Objective function: According to the literature [1]}, we treat top-K recommendation task as a binary classification problem, where 1 means that user has interacted with item, and 0 means that user has not interacted with item. In objective function, we use cross entropy as objective function, the formula is as follows Eq. REF :
\(\mathcal {J}=\sum _{(u,v)\in \mathcal {D}_{train}}\rm {BCELOSS}(\tilde{\emph {r}}_\emph {u,v},\emph {r}_\emph {u,v})+\lambda ||\mathcal {F}||_2^2\) 
